We implement a two-stage transition-based dependency parser following [1]}. First, an unlabeled tree is produced by vanilla transition-based approach. Then we train a separate SVM classifier to predict relation types on the tree in pre-order. For the 2nd-stage, apart from features in the 1st-stage, two kinds of features are added, including depth of head and dependent in the tree and the predicted relation between the head and its head.
